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Lockdown as a Strategy to Control COVID-19
Published in Hanadi Talal Ahmedah, Muhammad Riaz, Sagheer Ahmed, Marius Alexandru Moga, The Covid-19 Pandemic, 2023
Naheed Bano, Rizwan Ahmad, Zahid Khan, Majid Khan
Researchers are working, and a lot of epidemiology and economic-related literature with analysis methods, mathematical implications, and dynamic forces of transmittable diseases has been established from the last two decades. The characterization of any disease becomes more manageable by using mathematical modeling and epidemiology, whereas the economic structuring and epidemiology make the mechanisms understandable for policy-making and treatment [5, 67]. But most scientists and researchers also not tried to focus on macro-economic implications. The chaos may probably be created by cracks in health risks and economic interrelationship during epidemics. There are both short and long-run effects of epidemics on the economy. Still, what is needed is to find the treatment and preventive measures policies efficiency. The epidemic dynamics may be characterized by modeling susceptible-infected-susceptible design, which is the most effective epidemiological mathematical model [4, 68].
Issues and strategies of quantitative analysis
Published in John A. Bilorusky, Principles and Methods of Transformative Action Research, 2021
The point of this digression is not to divert our study of educational and community issues to theoretical physics, but to point out that, even in the so-called, very “hard” science of physics, physicists must decide which mathematical models and procedures to use. Mathematics is used to help us make sense out of the data, but mathematics cannot make the decisions for us, since we must decide how to use mathematics. That often involves critical thinking, exploratory seeking out of new data, and qualitative, reflective judgments. Physicists inevitably must exercise their judgment, in deciding which mathematical model to use to study any particular domain of reality. So, any application of a mathematical model or procedure is not necessarily valid or useful, even though the mathematics may be “precise.” Like the use of any model or method of interpreting data, they are potentially useful, or potentially limiting or misleading, and we must carefully and critically examine them in this light.
Ayurveda Renaissance – Quo Vadis?
Published in D. Suresh Kumar, Ayurveda in the New Millennium, 2020
Ayurvedic nosological data on 63 important vātaja (vāta-dominant), pittaja (pitta-dominant) and kaphaja (kapha-dominant) diseases were considered to verify the model. The V:P:K codes of these diseases were derived and their validity was tested through a correlation study using regression analysis with the least square method. An inverse relationship was found to exist between vāta and kapha in the kaphaja disease group (Figure 11.2). This finding is in agreement with evidence from ayurvedic theory. The V:P:K code is a novel finding that can be used for generating computer-based disease maps which can be used in experimental and clinical medicine. Although there are several reported studies of mathematical modeling in Chinese medicine (Ding and Wan 2008; Ming et al. 2010; Zhao et al. 2010; Han and Huang 2012; Kim et al. 2014) this is the first report of a mathematical model in Ayurveda.
A spatiotemporal computational model of focused ultrasound heat-induced nano-sized drug delivery system in solid tumors
Published in Drug Delivery, 2023
Farshad Moradi Kashkooli, Mohammad Souri, Jahangir (Jahan) Tavakkoli, Michael C. Kolios
Schematics of the DDS and different interactions of TSL/drug agents, along with a multi-compartment model of the current study, are shown in Figure 1. Integration of TSL and FUS provides a DDS via drug release at the tumor site, where TSLs are administrated intravenously and reach the tumor site via the circulatory system. TSLs enter the tumor microvessels where thermally triggered drug release is initiated due to temperature increase in the sonicated region inside the tumor due to acoustic energy absorption. The released drug extravasates rapidly into the tumor tissue and is then taken up by tumor cells. Therapeutic drug molecules have the potential to bind to plasma proteins in the blood, preventing drug agents from targeting cancer cells (Greene et al., 1983). The assumption is that free drug molecules can enter the cellular space; on the other hand, free drug molecules can be pumped out of cells based on multidrug-resistant traits of cells (El-Kareh & Secomb, 2000; Chabner & Longo, 2011). The present mathematical model has been developed according to a multi-compartment model in which each bio-physical medium is considered a compartment, and therapeutic agents are exchanged between these compartments.
Stimuli-sensitive nano-drug delivery with programmable size changes to enhance accumulation of therapeutic agents in tumors
Published in Drug Delivery, 2023
Mohammad Souri, Mohammad Kiani Shahvandi, Mohsen Chiani, Farshad Moradi Kashkooli, Ali Farhangi, Mohammad Reza Mehrabi, Arman Rahmim, Van M. Savage, M. Soltani
In vivo models can well estimate the efficiency of the current drug delivery system in the preclinical stages. However, it is very difficult to explain how therapeutic agents are distributed and how they interact with the biological environment, and their effect on cell death based on in vivo models. The mission of mathematical models is to investigate different methods and optimize them. This will reduce errors and the number of tests of in vitro and in vivo models, as well as reduce their costs; therefore, the clinical translation of successful will also be accelerated. The present study, as such, has developed a mathematical model that predicts the success of the current drug delivery system by considering the factors affecting the transport of therapeutic agents and their interactions. Due to the complexity of the proposed drug delivery system, the mathematical model includes detailed equations and parameters that are influenced by therapeutic conditions, temperature, and other functions. In the present study, it was found that if the size of the primary and secondary nanoparticles is optimally selected to control nano–bio interactions, which can suppress the proliferation of cancer cells for a long time. Therefore, the proposed mathematical model is a step forward in achieving targeted oncology and can be used for prediction in drug delivery processes.
Enrichment of plasma in platelets and extracellular vesicles by the counterflow to erythrocyte settling
Published in Platelets, 2022
Darja Božič, Domen Vozel, Matej Hočevar, Marko Jeran, Zala Jan, Manca Pajnič, Ljubiša Pađen, Aleš Iglič, Saba Battelino, Veronika Kralj-Iglič
Mathematical model is an important tool for interpretation of measurements. It provides insight into the mechanism why and how parameters influence the quantities of interest. For example, based on the model, the CP and the time of centrifugation can be estimated for an individual sample (Equation (4)) for which the highest yield of platelets and/or EVs can be expected (Equation (6)). The model was constructed based on the experimental part of this study, which was set by a previously used protocol that was equal for all samples [8]. It was however observed during the study that the volumes of EPP obtained by the same CP and time of centrifugation of blood differed considerably although the hematocrit values of the samples did not vary much. This indicated that the efficiency of centrifugation could be increased by individualization of the centrifuge setting. To achieve the optimal setting, the model is necessary. In the future, a prospective clinical study should be made to validate the prediction and possibly imply improvements in the model to finally get to a practical advice (a formula or a computer application) how to determine CP and the centrifugation time in clinical practice for a given sample, based on the results of the standard laboratory blood test.